--- /dev/null
+#include <math.h>
+#include <stdlib.h>
+
+void ml_predict_noNA(double* X, double* Y, int* n_, int* K_, double* alpha_, int* grad_, double* weight)
+{
+ int K = *K_;
+ int n = *n_;
+ double alpha = *alpha_;
+ int grad = *grad_;
+
+ //at least two experts to combine: various inits
+ double initWeight = 1. / K;
+ for (int i=0; i<K; i++)
+ weight[i] = initWeight;
+ double* error = (double*)malloc(K*sizeof(double));
+ double* cumDeltaError = (double*)calloc(K, sizeof(double));
+ double* regret = (double*)calloc(K, sizeof(double));
+
+ //start main loop
+ for (int t=0; t<n; t++ < n)
+ {
+ if (grad)
+ {
+ double hatY = 0.;
+ for (int i=0; i<K; i++)
+ hatY += X[t*K+i] * weight[i];
+ for (int i=0; i<K; i++)
+ error[i] = 2. * (hatY - Y[t]) * X[t*K+i];
+ }
+ else
+ {
+ for (int i=0; i<K; i++)
+ {
+ double delta = X[t*K+i] - Y[t];
+ error[i] = delta * delta;
+ }
+ }
+
+ double hatError = 0.;
+ for (int i=0; i<K; i++)
+ hatError += error[i] * weight[i];
+ for (int i=0; i<K; i++)
+ {
+ double deltaError = hatError - error[i];
+ cumDeltaError[i] += deltaError * deltaError;
+ regret[i] += deltaError;
+ double eta = 1. / (1. + cumDeltaError[i]);
+ weight[i] = regret[i] > 0. ? eta * regret[i] : 0.;
+ }
+
+ double sumWeight = 0.0;
+ for (int i=0; i<K; i++)
+ sumWeight += weight[i];
+ for (int i=0; i<K; i++)
+ weight[i] /= sumWeight;
+ //redistribute weights if alpha > 0 (all weights are 0 or more, sum > 0)
+ for (int i=0; i<K; i++)
+ weight[i] = (1. - alpha) * weight[i] + alpha/K;
+ }
+
+ free(error);
+ free(cumDeltaError);
+ free(regret);
+}